About Commvault

Commvault (NASDAQ: CVLT) is the gold standard in cyber resilience. The company empowers customers to uncover, take action, and rapidly recover from cyberattacks – keeping data safe and businesses resilient. The company’s unique AI-powered platform combines best-in-class data protection, exceptional data security, advanced data intelligence, and lightning-fast recovery across any workload or cloud at the lowest TCO. For over 25 years, more than 100,000 organizations and a vast partner ecosystem have relied on Commvault to reduce risks, improve governance, and do more with data.

Role Overview

We have an exciting opportunity to join our Business Technology Team! We are looking for a software engineer first—focused on writing clean code, designing robust systems, and delivering reliability at scale. You leverage AI to drive real business impact in two ways: building automation pipelines that ingest data, apply intelligence, and update downstream systems, and developing AI agents that reason, use tools, and take action. You move quickly to prototype and validate ideas, then harden solutions for production. You own the full stack end to end, including API design, cloud infrastructure, AI integration, business logic, evaluation, monitoring, and the feedback loops that continuously improve system performance.

Responsibilities

Re-engineer the process before automating it; map the workflow, cut the steps that shouldn't exist, then design the automation around the improved process, not the old one.
Build end-to-end automation that connects business inputs – emails, documents, events – to outputs like classified data, routed records, and updated systems, through an AI processing layer.
Design and build AI agent systems – from single-agent task executors to multi-agent pipelines where agents specialise, coordinate, and hand off.
Design human-in-the-loop governance and guardrails – confidence thresholds, approval gates, escalation paths, and hard limits on what an agent may do unsupervised.
Run AI operations – monitor for drift and hallucination, manage prompt and model versions, control token cost, and catch quality regressions before users do.
Integrate Azure OpenAI and other LLM services into production – prompt design, context management, response validation, tool use, and function calling.
Build RAG pipelines – ingestion, chunking strategy, embedding, vector store management, and retrieval tuning for real-world queries.
Build and run the REST APIs and Azure services behind every pipeline, integrate enterprise systems (CRM, ERP, comms) via their APIs and standard protocols like MCP, and write the business-rule and validation layers on top of AI output.
Tie every system to a business metric – productivity, cycle-time, or cost – instrument it, and report the impact you actually delivered.

Requirements

Essential Skills & Experience

+ Bachelor’s degree in Computer Science or related field
+ 2–4 years of software engineering experience building production systems
+ Strong fundamentals (algorithms, data structures, system design)
+ Proficiency in Python, C#, or Java; experience building REST APIs
+ Experience developing cloud-based applications (Azure preferred; AWS/GCP acceptable)
Proven ability to deliver end-to-end solutions (design deployment+ support)
+ Experience writing clean, maintainable, well-tested code

AI & Automation

+ Hands-on experience with LLMs (e.g., Azure OpenAI), including prompt design and output validation
+ Experience building AI-powered workflows (automation pipelines, RAG, or similar)
Familiarity with agent frameworks (e.g., LangChain, Semantic Kernel)

Execution & Mindset

+ Strong problem-solving skills and comfort with ambiguity
+ Ability to communicate technical concepts clearly
+ Self-starter with a learning mindset; adapts quickly to new tools and technologies
+ Strong written and spoken English

Preferred Skills & Experience

Vector DB internals, LLM observability, Fine-tuning, Multimodal AI, Salesforce / Dynamics 365 / Gainsight, Azure Data Factory, TypeScript / Node.js